Current progress of cerebral organoids for modeling Alzheimer's disease origins and mechanisms

Abstract Alzheimer's disease (AD) is a progressive, neurodegenerative disease that has emerged as a leading risk factor for dementia associated with increasing age. Two‐dimensional (2D) cell culture and animal models, which have been used to analyze AD pathology and search for effective treatments for decades, have significantly contributed to our understanding of the mechanism of AD. Despite their successes, 2D and animal models can only capture a fraction of AD mechanisms due to their inability to recapitulate human brain‐specific tissue structure, function, and cellular diversity. Recently, the emergence of three‐dimensional (3D) cerebral organoids using tissue engineering and induced pluripotent stem cell technology has paved the way to develop models that resemble features of human brain tissue more accurately in comparison to prior models. In this review, we focus on summarizing key research strategies for engineering in vitro 3D human brain‐specific models, major discoveries from using AD cerebral organoids, and its future perspectives.


| INTRODUCTION
Alzheimer's disease (AD) is a cognitive disorder that affects approximately 5.8 million Americans. It is characterized by memory loss, confusion, lack of awareness, and other symptoms that disrupt daily life and lead to a loss of independence. 1 AD mainly affects the elderly population with approximately 80% of cases associated with those 75 or older. 2 Unfortunately, there is no cure for AD, and the cost of care associated with AD patients can put an economic strain on caregivers. For example, one study reports average, monthly expenses are €2450 using the proxy good method and €3102 with the opportunity cost method, but averages vary based on the severity of AD. 3 AD can be classified into two main factions: Familial AD (FAD) and Sporadic AD (SAD). SAD comprises most AD cases, however, FAD is an early-onset subtype (symptoms seen in patients as early as their 40s or 50s) and affects less than 1% of the overall AD population. 4 Despite their varying genetic origins, FAD and SAD produce similar pathologies including amyloid beta (Aβ) plaques (specifically a higher ratio of Aβ42 to Aβ40), hyperphosphorylation of the microtubule-associated protein, tau (P-tau), aggregation of P-tau into neurofibrillary tangles (NFTs), abnormal endosomes, increased reactive oxygen species (ROS), neuronal inflammation, and apoptosis. 5 Significant progress has been made using various cell culture and animal models to understand the pathways behind FAD and SAD progression. Over the past 12 years, 7281 papers related to modeling AD have been published across a range of journal categories (Web of Science; Figure 1a,b). Both the publication number and citation number Sai Sreenivasamurthy, Mahek Laul, and Nan Zhao contributed equally to this study. increased yearly (Figure 1c), indicating a rise in popularity of designing more accurate AD brain models as reliable platforms. 2D and 3D culture models have demonstrated Aβ plaque and NFT formation, [6][7][8][9][10][11][12][13] however, the structural complexity of the cellular networks is lacking, making results difficult to fully translate in vivo. Animal models have been more successful in modeling AD due to their high physiological relevance, 14 but these models are not able to fully recapitulate the structure, function, and cellular diversity of human brains.
From advances in tissue engineering and stem cell technology, the development of stem cell-derived cerebral organoids has provided new strategies to accurately and efficiently model AD pathways in vitro by invoking similar pathologies observed in AD patients. Organoids are self-assembled 3D structures that mimic in vivo characteristics of a chosen organ; their emergence provides more sophisticated methods to examine tissue structure, pathology, and drug delivery mechanisms. AD organoid models can accurately replicate disease characteristics seen in AD patients and be tailored to mimic FAD, SAD, or alternative AD mechanisms based on risk-associated genes in the initial cell sources or through manipulation of the microenvironment as the organoids mature. 15 Additionally, organoid platforms may reduce the reliance on animal models and associated costs, therefore proving to be more ethical and economical. 16 This short review discusses the current advancements in FAD and SAD organoid models along with future perspectives in this field.

| AD PATHOLOGY
Many factors could contribute to the development of AD such as genetic factors, environmental toxins, infections, and aging ( Figure 2a). FAD patients may begin to exhibit symptoms between their 40s to mid-50s. 17 In the case of SAD, the first symptoms appear in the mid-60s. 18 Once symptoms show, the progression follows the typical trends associated with AD, though there is variability in which symptoms appear first. In most cases, issues relating to memory and mild cognitive impairment (MCI) are seen in the early stages of AD. MCI includes difficulty with thinking and judgment such as losing train of thought, losing items, impulsive decision-making, and forgetting important events or appointments. However, the severity of these symptoms is lower and they will not interfere with daily life and personal relationships. 19 As a patient progresses from mild to moderate AD, memory issues become more severe, leading to repetitive statements/questions, inability to recognize loved ones, difficulty in learning new information/tasks, or inability to create new memories.
The patient may also become unaware of their surroundings and therefore, become paranoid or delusional. In the final stages of AD, there is a loss of motor control, affecting the patient's ability to communicate, eat, and control their bowels and bladder. Other symptoms may include seizures, increased sleep, and incoherent noises such as groaning and grunting. The exact timeline for disease progression varies from patient to patient. However, most patients do not survive for longer than 4-8 years after being diagnosed clinically, with diagnosis only being confirmed with postmortem neuropathological analysis. 20 The hallmark pathologies of AD include the formation and accumulation of extracellular Aβ plaques around neurons, P-tau, and aggregation of intracellular P-tau into neurofibrillary tangles (NFT; Figure 2a). Accumulation of Aβ plaques and NFTs may affect neural viability and compromise the effectivity of the blood-brain barrier (BBB). 21 The BBB is highly selective and is only permeable to certain small lipophilic molecules, oxygen, and carbon dioxide. Aβ plaque formation disrupts surrounding endothelial cells as well as cells adjacent to the BBB such as pericytes, smooth muscle cells, and glia, yielding a "leakier" BBB to blood cells and an overall decline in BBB functionality. [21][22][23] The neuroinflammation and reactive gliosis caused by the accumulation of Aβ plaques also lead to neuronal and synaptic dysfunction as a result of the inflammatory cytokines released by microglia and astrocytes, producing the cognitive defects seen in AD. 24 The genes affecting FAD and SAD vary but result in similar pathologies that characterize AD. The gene coding for APP is often mutated in FAD patients, along with PSEN1 and PSEN2 (Table 1). F I G U R E 2 Risk factors of Alzheimer's disease (AD) and associated pathology at cellular and molecular levels. (a) Schematic summary of AD-associated factors. Genetic, nongenetic, and environmental factors contribute to the development of AD and can affect the functions of varying types of brain cells. Hallmark pathologies for AD include Aβ accumulation, formation of NFTs, BBB damage, and neuronal death. (b) Amyloidogenic pathway (left) and non-amyloidogenic pathway (right) of amyloid precursor protein (APP) breakdown. (c) Pathology of NFT aggregation. In normal pathology, tau proteins remain bound to microtubules assisting in structural integrity and cell-to-cell communication. In AD pathology, tau proteins become hyperphosphorylated and eventually aggregate to form NFTs in neurons. (d) Activated microglial response. With Aβ plaque accumulation, microglia become triggered to release pro-inflammatory cytokines which compromise neuronal viability. Created with BioRender.com One gene that is commonly found to influence SAD is APOE which codes for apolipoprotein E. The ε3 allele of APOE is the version typically carried, however, the presence of the ε4 allele poses as a risk factor for AD as it is associated with increased Aβ plaque formation.
Other genes are also thought to be responsible for influencing SAD development ( Table 2). 25 Amyloid precursor protein (APP) is a transmembrane protein whose role is not completely understood. Under normal circumstances, APP is broken down by the nonamyloidogenic path in which α-secretase will locate the Aβ domain on the protein and cleave it between the 16th and 17th amino acid. This produces a soluble neuroprotective N-terminal fragment called soluble amyloid precursor protein (APPsα). 26,27 The C-terminal fragment (C83), which is still attached to the membrane, will be further cleaved by γ-secretase.
These two cuts result in a p3 peptide and intracellular domain of APP (AICD) which does not pose a threat to brain tissues (Figure 2b). 27 In AD patients, β-secretase is the primary cleaver of the APP protein.
β-Secretase locates the Aβ domain and cleaves it at the N-terminus; the cleaved part of the molecule is APPsβ, and the fragment remaining in the membrane is C99. 27,28 γ-Secretase functions as normal and cleaves the C-terminus side of the domain, resulting in the entire Aβ domain dislodging as one insoluble piece, most commonly as isoforms Aβ40 and Aβ42. Aβ40 is generally benign, but Aβ42 is highly self-aggregating. 27,29 This mechanism comprises the amyloidogenic pathway which is seen at much higher rates in AD patients. This is evidenced by the accumulation of the insoluble Aβ peptides around neurons in AD patients (Figure 2b). Although the exact mechanism of increased β-secretase activity in AD patients is unknown, it is known that the Swedish mutation of substituting methionine for leucine at the P1 position of APP enhances β-secretase cleavage. 30 It is speculated that the products of the amyloidogenic pathway may have cell signaling mechanisms that also enhance β-secretase activity.
α-Secretase expression does not decrease, rather there is increased competition between the two enzymes, and the APP mutation provides an advantage to β-secretase. 31 The tau protein has many sites with phosphorylation potential. In a healthy physiological environment, the tau proteins are phosphorylated and dephosphorylated by kinases and phosphatases, respectively ( Figure 2c). In AD brain tissue, combinations of kinases, cdk5/GSK3, and calcium calmodulin kinase II are largely responsible for the increased rate of proline-directed phosphorylation. Proteins responsible for dephosphorylation such as phosphatase 2A are unable to balance the phosphorylation. Thus, the tau proteins become hyperphosphorylated and change shape to form paired helical filaments (PHFs). 32,33 Aggregation of PHFs leads to the development of insoluble NFTs. Tau proteins also lose their functionality to bind cytoskeletal microtubules. 34 The mechanism by which tau proteins become susceptible to hyperphosphorylation is yet to be confirmed, however, one proposed mechanism is that calpain cleaves tau at the N-terminus, changing the conformation of the protein from unfolded to a β-sheet. This conformational change leaves the C-terminus vulnerable to cleavage by caspase.
Once cleaved, tau becomes more susceptible to hyperphosphorylation ( Figure 2c). 33 Additionally, studies have shown a correlation between Aβ plaques and NFT formation, suggesting that there may be a synergistic effect involving these two pathologies. 35 The buildup of Aβ plaques and NFTs may eventually compromise neuronal viability by microglial activation and high production of pro-inflammatory cytokines. While early stimulation of microglia provides a more defensive mechanism to remove Aβ debris, a continuous buildup may shift microglia to take a more pro-inflammatory stance, leading to downstream neuroinflammation and apoptosis ( Figure 2d). 36,37 3 | MODEL SYSTEMS FOR AD Common model systems that have been used for assessing the mechanism of AD include animal models, 2D cell culture models, 3D organoid models, as well as computational simulations (in silico model).   primates, and most notably, mice. Modeling with invertebrates can be relevant to human physiology by studying the molecular pathways underlying AD. There is also an advantage in efficiency as invertebrates tend to reproduce much faster than mammals. Fruit flies, nematodes, and zebrafish all have genes that are either homologs or orthologs of some of the genes relevant to AD found in humans ( NFTs were also not observed in this model. 48 Nontransgenic or injection AD models are often used to study SAD using an intracerebroventricular infusion of streptozotocin (ICV-STZ). Treatment with this chemical does not contribute to Aβ or P-tau production but causes significant cognitive impairment likely due to oxidative stress. 49 Unfortunately, the trend remains the same, and none of the models fully recapitulate the pathology of AD as in humans. There are additional disadvantages to using mouse models, one being that their brains do not function identically to human brains. Mice and humans share about 85% of their genomes, leaving a 15% translational gap that may include substantial differences. Also, human brains consist of roughly an equal proportion of neurons ($1.38 billion neurons) 50 and glial cells, while mouse brains are roughly 70% neurons ($70 million neurons) and 30% glia. 51 These differences will impact how AD progresses within mice and human brains.
In addition to mice, nonhuman primates including rhesus monkeys (Macaca mulattas), stump-tailed macaques (M. arctoides), mouse lemurs (M. murinus), common marmosets (C. jacchus), and cynomolgus monkeys (M. fascicularis) have been used to study SAD. These models can be advantageous for studying naturally aged primates as they more closely resemble the aged, human brain. For example, nonhuman primate models have shown tau protein accumulation as well as Aβ deposits. [52][53][54][55][56] Cognitive deficits linked to AD symptoms are also observed in nonhuman primate models. While this is extremely relevant to studying AD pathogenesis, there are still key differences in AD pathology between nonhuman primates and humans. In humans, the hippocampus is the main region where Aβ plaques are deposited.
However, in rhesus macaques and common marmosets, plaques tend to accumulate in the limbic cortex and temporal cortex, respectively. 53,55 P-tau also tends to accumulate in the hippocampus in F I G U R E 3 Model systems for Alzheimer's disease. (a) Animal models. Genetically engineered animal models that express ADrelated genes. Two most popular animal models for AD are rodents and nonhuman primates. (b) 2D model systems. Mono-culture on a petri dish, co-culture, or triculture of brain cells or a transwell insert using primary cells from human patients or induced pluripotent stem cells (iPSCs) derived brain cells. (c) Brain organoid models and brain organ on a chip model. (d) Comparison of animal models, 2D models, and organoids models. À, none; +, low; ++, medium; +++, high

T A B L E 3 Genes relevant to AD across observed species
Human/primate/mouse Fruit fly Nematode Zebrafish MAPT dTau ptl-1 mapta/maptb humans while P-tau accrues in the cerebral cortex in mouse lemurs. 52 Additionally, humans can display AD pathology without cognitive impairment, but both aspects are typically seen together in stumptailed macaques. 56 In sum, nonhuman primate models can prove to be advantageous due to natural and similar AD progression to humans, but the pathological differences, the lack of samples due to longer lifespans, and the high costs associated with them cannot be ignored.
And, as with all animal models, there are ethical concerns with testing and even more so when disease factors must be introduced.

| 2D culture models
Two-dimensional (2D) in vitro cell cultures have been used in research for over a century. 57 They consist of cells grown in cell culture wells or trans-wells ( Figure 3b) usually coated with compounds such as fibronectin, laminin, and collagen which allow for better cell adhesion and support differentiation. 58 The key advantages of 2D models include simplicity, low cost, and high-throughput screening. Unfortunately, 2D models are not suitable for modeling the complexities of AD pathology as they lack the structure and function of the native brain. Despite those shortcomings, typical AD pathologies such as the formation of Aβ plaques and NFTs have been replicated in 2D models. 6

| 3D culture models
The formation of 3D cultures using hydrogels as extracellular support introduced advancements with in vitro modeling, including the formation of neurospheroids which are a cluster of brain cells that provide some brain-related function. Unlike cerebral organoids, neurospheroids cannot self-assemble, lack cellular diversity, and do not contain tissue architecture that resembles in vivo brain formation, but they still serve as useful systems for modeling pathologies. 59  The integration of microfluidic-based platforms for culture systems provides certain advantages in 3D culturing such as modeling blood flow, investigating interactions between spheroids, and understanding the effects of multiple organ systems (Figure 3c). Park et al.
introduced a 3D microfluidic device incorporating Matrigel-filled chambers for housing APP and PSEN1-mutated neuron/astrocyte cultures with microglia. 12 In contrast to their 2D microfluidic system, the 3D system contained increased Aβ42 aggregation and P-tau formation. However, additional experiments also showed migration of microglia to induce neuron/astrocyte loss via IFN-γ and TLR4 mechanisms. Microglia were also found to substantially increase the production of TNF-α and nitric oxide (NO) inflammatory markers that contribute to these mechanisms. 12 Jorfi et al. produced neural spheroids in microwell arrays, and similarly, clusters demonstrated overexpression of APP and PSEN1 after 9 weeks. Interestingly, the spheroids contained dendrites extending outward rather than inward, suggesting this model could be used to study signaling networks between adjacent spheroids. 13 Tunesi and colleagues took the first steps toward designing a multi-organ-on-a-chip device to recapitulate the microbiota-gut-brain axis (MGBA) and evaluate its influence on AD pathology. Their platform was demonstrated to be suitable for hydrogel-based cultures and allowed perfusion of media that mimicked mechanical cues necessary for stimulating certain cell behaviors. Additionally, their device allowed for interconnected units to model the dependency among multiple organ systems. Their findings revealed increased Aβ42 production in APP-mutated H4 neuroglioma cells using their microfluidic platform. 61 In addition to modeling AD, cerebral organoids and chip-based models have been used for drug delivery, efficacy testing, and toxicity assessments for several cognitive diseases. 62 Overall, cerebral organoids demonstrate themselves as more sophisticated models in comparison to the 2D culture or animal models as previously described and provide higher accuracy for modeling neurodegenerative diseases. Alongside AD, organoids have been used to model Parkinson's, 95,96 Huntington's, 97,98 and CJD. 99

| Genetically induced FAD models
As mentioned previously, FAD is a hereditary form of AD with mutations of APP, PSEN1, and PSEN2, leading to Aβ buildup (specifically a higher ratio of Aβ42 to Aβ40), greater P-tau and NFT deposition, and ROS release ( Figure 2). 100 106 The presence of 5hmC during embryonic brain development correlates to maturation through neural differentiation, cell functions, and structural development. AD organoids showed an overall reduction of 5hmCs through the 112-day period and upregulated genes associated with AD, therefore demonstrating the potential onset of FAD due to a lack of 5hmC during fetal brain development. 106 The timeline-like dependency seen in other studies was also modeled here to mark the progression of embryo development in terms of DNA structural changes with 5hmC levels.

| Genetically induced SAD models
SAD has been considered more difficult to model due to the lack of associated mutations and the influence of external stimuli, 113 yet, it consists of similar pathologies associated with FAD such as Aβ accumulation, P-tau, NFT formation, and neuronal loss (Figure 2).
Symptoms in SAD patients are typically seen later than in patients diagnosed with FAD and its onset is strongly linked to APOE4. 18 Therefore, many established models of SAD organoids utilize iPSCs derived from AD APOE4 carriers or use CRISPR/Cas9 to edit genomes to contain the ε4 isoform. [114][115][116][117][118] F I G U R E 5 Characterization of brain organoids. (a) Different biotechniques used to characterize the differentiation, compartmentalization, and maturation of cerebral organoids. Panel on the left lists protein detection techniques such as RT-PCR and western blot/ELISA used to quantify the expression of target proteins, and mass spectroscopy to sample the organoid proteome. Panel on the right lists methods such as histological stains or antibody-based labeling used to visually classify tissue for the presence, distribution, and quantity of specific proteins. (b) Outline of common proteins previously quantified to distinguish the presence of certain brain regions within cerebral organoids. Proteins are listed based on regions they are associated with and their approximate location within the forebrain, midbrain, or hindbrain. Created with BioRender.com Lin et al. used CRISPR/Cas9 to edit the APOE3 in iPSCs to the APOE4 allele and generate independent cultures of neurons, microglia, and astrocytes. 114 In comparison to the control, neurons expressed increased synapse activity and 20% higher Aβ42 levels.
Also, microglia had reduced Aβ42 phagocytic activity and increased inflammatory expression, and astrocytes also displayed reduced efficiency in clearing Aβ42. Cerebral organoids containing the APP mutation and Aβ42 aggregation were co-cultured with APOE4 microglia and results demonstrated increased Aβ42 formation and P-tau. Additionally, 6-month SAD patient-derived organoids with APOE4 to APOE3 converted genomes expressed reduced Aβ42, highlighting the influence of APOE4 in further promoting AD. 114  as AD. 119 The authors mimic BBB structure and behavior using a selfassembled tri-culture of brain endothelial cells, mural cells, and astrocytes in Matrigel. All cell lineages were derived from iPSCs with homozygous APOE3, APOE4, or a heterozygous combination. The highest levels of F I G U R E 6 Summary of key protocols for engineering AD brain organoids. Previously used methods and compounds are listed based on FAD mutations, SAD APOE4-related, and alternative mechanisms related to AD. Steps are separated based on common organoid formation stages such as EB formation and differentiation. Created with BioRender.com Aβ were produced by BBBs developed from homozygous APOE4 followed by the heterozygous combination. 118 Similarly, Chen et al. produced a cortical organoid model to observe BBB leakage typically observed in SAD. As cerebral organoids currently lack vasculature and blood flow, BBB leakage was emulated by exposing the organoid to human serum for 12 days. As hypothesized, Aβ accumulation increased in serum-treated organoids through increased expression of betasecretase 1 (BACE), one of the proteins responsible for cleaving APP to form Aβ aggregates. Additionally, higher P-tau was also observed via the GSK3α/β tau protein-kinase mediated pathway. 120

| Alternative mechanisms used for AD models
Additional studies invoke AD pathology by exploring alternative signaling pathways instead of manipulating genes directly associated with FAD or SAD. 121 Other researchers introduced novel AD platforms or methods to broaden disease analysis, [128][129][130] Chen et al. provided the first proteomic filing for neurospheroids using mass spectroscopy. Protein expression changes linked to axon development, gliogenesis, and immune response were found to mimic those found in post-mortem AD tissue.
While the iPSC-derived neurospheroids contained identical genomes to those found in post-mortem tissues, the neurospheroids were not associated with any particular brain region while the post-mortem tissue was specifically removed from the frontal cortex, interior cortex, and cerebellum. 128 130 Overall, these alternative models provide their unique advantages and mechanisms to similarly characterize AD without the genetic modifications associated with FAD or SAD.

| Engineering brain organoids with vasculature
Although cerebral organoids have been proposed as a superior alternative to animal models, they come with their own set of limitations.
One issue that greatly hinders the growth potential of organoids is the lack of overlying meninges and vasculature. These structures provide support for brain development and their absence creates batchto-batch variation. 86 The lack of vasculature in cerebral organoids is concerning for several reasons. Without a significant vascular system, the organoid is entirely dependent on diffusion from its extracellular matrix for oxygen and nutrients. As the organoid grows, diffusion is no longer sufficient for transporting enough oxygen and nutrients to the center of the organoid, leading to necrosis and eventually rendering the organoid unsuitable for experimentation. 131 This poses a challenge for modeling AD in organoids due to a lack of aging in comparison to in vivo AD brains. Instead, the cerebral organoids more closely resemble a fetal brain. Because this issue has not been fully resolved, it is difficult to estimate the time duration necessary to better recapitulate AD pathology as seen in the adult human brain. Another potential solution is to precast empty channels in the brain organoids at the early stage and seed those channels with endothelial cells as brain blood vessels. Finally, the rapid development of 3D printing systems will likely enable the engineering of different vascularized tissue, including cerebral organoids, in the near future.

| Introducing cellular diversity
Another limitation of current cerebral organoid models is the lack of cell diversity, especially the lack of microglia. Aβ plaques have been shown to stimulate microglia, causing inflammatory responses that contribute to neuronal loss and damage to synapses (Figure 2d).
Microglia also participate in the process of degrading Aβ plaques and thus are essential for modeling AD pathology. 36,37 Culturing differentiated microglia with a maturing organoid is one approach to address this issue. Another method is to grow primitive macrophage progenitors (PMPs) with NPCs at the beginning stages of organoid growth, as done by Xu et al. 133 As the organoid matures, the surrounding progenitors will differentiate concomitantly. This strategy also allows for control over the ratio of microglia to neurons for more homogeneous organoids that match the ratio seen in vivo. Song et al. co-cultured microglia-like cells with dorsal-ventral organoids, and phase-contrast images overlapped with fluorescent images showed integration of the microglia into the organoids. They were able to use their model to study the inflammatory responses of the microglia when exposed to Aβ plaques. 134  This process created a distinct BBB, and its functionality was tested through treatment with mercury ions. The organoids with the BBB demonstrated low permeability to the mercury ions in comparison to the control group (no BBB, traditionally grown organoids). 135 Co-culturing, also seen in other investigations discussed earlier, shows strong promise in creating a more accurate model of the human brain.
The method of co-culturing progenitor/precursor cells better mimics the process of differentiation in vivo, meaning the cellular interactions occurring between the differentiating cells are more relevant and more likely to mirror normal brain development.
Cho et al. cultured cerebral organoids in a decellularized brain ECM taken directly from human patient samples. This method allowed greater cell diversity to develop in the organoid such as the inclusion of a higher microglial population. A more complex structure including several ventricle-like structures and a thicker cortical layer were also observed. 136 The more intricate structure suggests using a human brain ECM may provide the support that Lancaster's model was lacking due to missing meninges. This method of growing cerebral organoids seems ideal as they are in a similar environment in which the brain develops in vivo, but even if researchers use human brain samples to replicate this model, they cannot guarantee qualitative consistency across all samples.

| Alternatives to Matrigel for generation and maintenance of organoids
Another limitation of organoids is their batch-to-batch variability. 137 The matrix used in culturing organoids is a significant factor contributing to this variability. For example, Matrigel is the most common matrix used for embedding organoids, but Matrigel has a high batch-to-batch variability regarding its composition and mechanical properties, and its contents are not well characterized. 138  Using synthetic hydrogels provides more control over the environment in which the cerebral organoids grow and thus allows for less batch-to-batch variability. For example, Ranga et al. generated a PEG-based synthetic hydrogel to grow cerebral organoids. 141 Compared to cerebral organoids grown in Matrigel, those grown in the synthetic hydrogel were more even, albeit slightly smaller than those grown in Matrigel. Lindborg et al. also generated a synthetic hydrogel composed of sodium hyaluronan and chitosan, termed Cell-Mate3D. 142 As the contents of these synthetic hydrogels are defined, they allow for more widespread use of organoids in downstream applications.
Another limitation of using Matrigel is that it does not fully represent the complexity of the CNS environment. 143 To address this, studies have synthesized hydrogels from decellularized brain ECM.

Simsa et al. used a decellularized adult porcine brain ECM (B-ECM)
for growing hESC-derived brain organoids in comparison with Matrigel. 144 On day 10 of development, they saw more uniform growth in the organoids grown in B-ECM hydrogel. However, on day 40, no differences were observed between the two groups. This uniform growth may be beneficial for studying brain development or disease pathogenesis. Cho et al. generated organoids grown in decellularized ECM from human brain tissue, which better mimics the compositions in brain ECM. Organoids were cultured within microfluidic chips to allow for fluid flow to resemble cerebrospinal fluid flow and demonstrate more reproducible results. 136 Organoids grown in their brain ECMs had enhanced growth, differentiation, cortical layer development, and electrophysiology compared to those grown in Matrigel, but the batch-to-batch variability was only improved with the use of their microfluidic chip. Therefore, the development of alternative hydrogels for embedding cerebral organoids is an important area of study.

| Multi-organ models
Although AD pathologies are primarily associated with the central nervous system no tissue or organ in the human body is completely isolated from other organs. Several studies link the gut microbiome, kidneys, and heart to AD pathology, cognitive impairment, and/or brain inflammation. [145][146][147][148][149][150][151][152][153] A study by Cattaneo et al. recognized that patients suffering from cognitive impairment and brain amyloidosis also had an abundance of the proinflammatory gut microbiome taxon genera Escherichia and Shigella, and a reduction of anti-inflammatory taxon E. rectale. They hypothesized that the composition of the gut microbiome may have some effect on brain inflammation, which would contribute to brain amyloidosis and potentially neurodegeneration. 147 Zhan et al. studied brain samples from deceased AD patients and found lipopolysaccharides and E. coli in the brain parenchyma of all samples in higher amounts than in those control samples. 152 Patients with chronic kidney disease have been shown to have concentrations of urea, nitrogen, and creatinine up to 10 times higher than normal in areas of the brain relating to cognition. 148 Heart failure or cardiac insufficiency can cause irregular vasoconstriction leading to more narrow microvasculature, effectively reducing the amount of oxygen going to the brain which is well known to cause cognitive impairment. 154 Although these findings are not directly correlated with AD, they show the need for more complex models involving more than only cerebral organoids to better understand mechanisms of cognitive impairment which is the most abundant symptom of AD. For example, as mentioned previously, Tunesi et al. designed a multi-organ-on-a-chip platform to model the MGBA for exploring the potential interplay between different organ systems. 61

| CONCLUSION
Cerebral organoids provide the next-generation platform for modeling the origins and mechanisms of AD progression and for screening effective treatments. Their ability to capture the development and architecture of human neuronal tissues is unparalleled to previous 2D cultures and animal models, thereby offering a more accurate model system. Drawbacks such as a lack of vasculature, cellular diversity, and a young developmental age will need to be addressed to develop more robust platforms for advanced screening. However, current progress to overcome these limitations provides a bright outlook for producing more conclusive, in-depth studies for AD and other neurodegenerative diseases.